qmotif: determination of telomere content from whole-genome sequence data

Oliver Holmes, Katia Nones, Yue Hang Tang, Kelly A. Loffler, Michael Lee, Ann-Marie Patch, Rebecca A. Dagg, Loretta M. S. Lau, Conrad Leonard, Scott Wood, Qinying Xu, Hilda A. Pickett, Roger R. Reddel, Andrew P. Barbour, Sean M. Grimmond, Nicola Waddell, John Pearson

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation
Changes in telomere length have been observed in cancer and can be indicative of mechanisms involved in carcinogenesis. Most methods used to estimate telomere length require laboratory analysis of DNA samples. Here, we present qmotif, a fast and easy tool that determines telomeric repeat sequences content as an estimate of telomere length directly from whole-genome sequencing.

Results
qmotif shows similar results to quantitative PCR, the standard method for high-throughput clinical telomere length quantification. qmotif output correlates strongly with the output of other tools for determining telomere sequence content, TelSeq and TelomereHunter, but can run in a fraction of the time—usually under a minute.

Availability and implementation
qmotif is implemented in Java and source code is available at https://github.com/AdamaJava/adamajava, with instructions on how to build and use the application available from https://adamajava.readthedocs.io/en/latest/.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
Original languageEnglish
Article numbervbac005
Number of pages3
JournalBioinformatics Advances
Volume2
Issue number1
DOIs
Publication statusPublished - 31 Jan 2022

Keywords

  • telomere content
  • whole-genome sequence data
  • qmotif
  • DNA

Fingerprint

Dive into the research topics of 'qmotif: determination of telomere content from whole-genome sequence data'. Together they form a unique fingerprint.

Cite this